Bibliographic record
Abstract
La guerre que l’on se prépare à faire est toujours une guerre virtuelle ; c’est une anticipation que l’on reproduit sur les terrains d’exercice sans jamais pouvoir l’imiter parfaitement. La difficulté est encore plus grande lorsqu’on perçoit à partir du milieu du xix e siècle que sous la poussée de changements considérables et rapides dans les sociétés de l’époque, cette guerre future sera forcément très différente de la dernière que l’on a menée. On met donc en place en France après 1871, à l’imitation de l’armée prussienne, toute une structure de simulation expérimentale de la guerre dont on espère qu’elle permettra de se préparer au mieux au grand conflit futur. Le résultat concret est très mitigé, mais cet effort aura au moins permis de former une génération d’officiers à analyser et débattre, ce qui sera essentiel pour obtenir la victoire.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.962 | 0.962 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".